Automating an industrial process is often difficult and complex, and often requires substantial efforts to optimize the process for a particular application. Industrial processes, in particular, often incorporate multiple equipment, machines and associated control systems, and often there is very little integration of these systems to facilitate the overall control of the process by a limited number of individuals or entities.
For example, in the oil & gas industry, drilling processes often require the interaction of and control over multiple control systems and equipment involved in drilling a well bore. A hoist system is used to support a drill string with a drill bit and multiple lengths of drill pipe, and a top drive system is used to rotate the drill pipe, and consequently, the drill bit. A mud circulation system driven by a mud pump circulates drilling fluid or mud down the well bore to lubricate and cool the drill bit and carry away drill cuttings, and in many instances, the drilling fluid drives a down hole bit motor to further rotate and/or steer the drill bit. An autodriller is often used to coordinate some of these operations; however, in conventional drilling rigs, much of the drilling process still involves a substantial amount of manual control and coordination of the individual systems and sub-systems in a drilling rig, often requiring the efforts of multiple personnel.
Furthermore, it has been found that due to variances between different applications, systems, sub-systems, equipment, sensors, machinery, and even variances in well bores and subsurface topology, no single algorithm is capable of managing or optimizing the entire drilling process for all possible applications.
Therefore, a substantial need continues to exist in the art for an improved manner of automating industrial and oil & gas processes, and in particular, drilling processes.